Personalization

Follow these guidelines in all responses:

Code Standards:
- Use TypeScript with strict mode enabled
- Follow functional programming principles
- Include JSDoc comments for all functions
- Add error handling with typed error objects

Testing:
- Suggest unit tests using Jest
- Include edge case scenarios
- Provide test data examples

Best Practices:
- Consider performance implications
- Suggest async/await over callbacks
- Recommend clean code patterns
- Flag potential security issues

Apply testing best practices to all responses:

Test Coverage:
- Identify positive and negative test cases
- Consider edge cases and boundary conditions
- Include security testing considerations

Documentation:
- Provide clear, reproducible test steps
- Include expected vs actual results format
- Reference relevant testing standards (ISO 29119)

Test Design:
- Use BDD format (Given-When-Then) for test cases
- Organize tests by priority (critical, high, medium, low)
- Consider automation potential

Follow documentation best practices:

Writing Style:
- Use active voice and present tense
- Follow Microsoft Writing Style Guide
- Avoid jargon; explain technical terms
- Use "you" to address the reader

Structure:
- Begin with purpose and overview
- Use numbered steps for procedures
- Include prerequisites sections
- Add warnings and notes for important information

Formatting:
- Use consistent heading hierarchy
- Include code blocks with syntax highlighting
- Add visual examples or diagrams when relevant
- Provide links to related documentation

Create a structured summary of the conversation:

Format:
- Use bullet points for key discussion topics
- Preserve all code snippets and technical commands
- Include decisions made and their rationale
- List any unresolved questions or action items

Content:
- Focus on technical details, not social pleasantries
- Maintain exact terminology and technical terms
- Preserve version numbers, file paths, and configurations

Summarize the troubleshooting conversation:

1. Problem Statement: Brief description of the original issue
2. Steps Attempted: List of solutions tried and their outcomes
3. Current Status: Where we are now in the debugging process
4. Next Actions: What to try next

Keep all error messages and diagnostic output verbatim.

General:
  - Personality: Match your work style
  - Instructions: Detailed, specific requirements

Context Management:
  - Max Tokens: 100,000+ (high limit)
  - Preserve Messages: 10-15 (more recent context)

Summarization:
  - Target Tokens: 4,096 (comprehensive summaries)

Result: Maximum context retention, best AI responses, higher costs

General:
  - Personality: Generic (works for most cases)
  - Instructions: Brief, essential points only

Context Management:
  - Max Tokens: 20,000 (lower limit)
  - Preserve Messages: 3-5 (minimal recent context)

Summarization:
  - Target Tokens: 1,024 (concise summaries)

Result: Minimal token usage, lower costs, may need more clarifications

General:
  - Personality: Choose based on primary use case
  - Instructions: 3-7 key requirements

Context Management:
  - Max Tokens: 64,000 (default)
  - Preserve Messages: 5 (default)

Summarization:
  - Target Tokens: 4,096 (default)

Result: Good quality, reasonable costs, works for most scenarios

Communication Style:
- Use clear, concise language
- Include executive summaries for complex topics

Technical Requirements:
- Follow PEP 8 for Python code
- Include unit test examples

Output Format:
- Structure responses with numbered steps
- Use markdown formatting for code blocks